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The electric autonomous dial-a-ride problem

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  • Bongiovanni, Claudia
  • Kaspi, Mor
  • Geroliminis, Nikolas

Abstract

In the Dial-a-Ride-Problem (DARP) a fleet of vehicles provides shared-ride services to users specifying their origin, destination, and preferred arrival time. Typically, the problem consists of finding minimum cost routes, satisfying operational constraints such as time-windows, origin-destination precedences, user maximum ride-times, and vehicle maximum route-durations. This paper presents a problem variant for the DARP which considers the use of electric autonomous vehicles (e-ADARP). The problem covers battery management, detours to charging stations, recharge times, and selection of destination depots, along with classic DARP features. The goal of the problem is to minimize a weighted objective function consisting of the total travel time of all vehicles and excess ride-time of the users. We formulate the problem as a 3-index and a 2-index mixed-integer-linear program and devise a branch-and-cut algorithm with new valid inequalities derived from e-ADARP properties. Computational experiments are performed on adapted benchmark instances from DARP literature and on instances based on real data from Uber Technologies Inc. Instances with up to 5 vehicles and 40 requests are solved to optimality.

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  • Bongiovanni, Claudia & Kaspi, Mor & Geroliminis, Nikolas, 2019. "The electric autonomous dial-a-ride problem," Transportation Research Part B: Methodological, Elsevier, vol. 122(C), pages 436-456.
  • Handle: RePEc:eee:transb:v:122:y:2019:i:c:p:436-456
    DOI: 10.1016/j.trb.2019.03.004
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    10. Cortés-Murcia, David L. & Prodhon, Caroline & Murat Afsar, H., 2019. "The electric vehicle routing problem with time windows, partial recharges and satellite customers," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 130(C), pages 184-206.
    11. Bongiovanni, Claudia & Kaspi, Mor & Cordeau, Jean-François & Geroliminis, Nikolas, 2022. "A machine learning-driven two-phase metaheuristic for autonomous ridesharing operations," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 165(C).
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